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import json
import subprocess
import requests
from llama_cpp import Llama
import gradio as gr
url="https://huggingface.co/TheBloke/WizardLM-13B-V1.2-GGUF/resolve/main/wizardlm-13b-v1.2.Q4_0.gguf"
response = requests.get(url)
with open("./model.gguf", mode="wb") as file:
file.write(response.content)
print("Model downloaded")
command = ["python3", "-m", "llama_cpp.server", "--model", "./model.gguf", "--host", "0.0.0.0", "--port", "2600"]
subprocess.Popen(command)
print("Model ready!")
#llm = Llama(model_path="./model.gguf")
#def response(input_text, history):
# output = llm(f"Q: {input_text} A:", max_tokens=256, stop=["Q:", "\n"], echo=True)
# return output['choices'][0]['text']
def response(message, history):
#url="https://afischer1985-wizardlm-13b-v1-2-q4-0-gguf.hf.space/v1/completions"
url="http://0.0.0.0:2600/v1/completions"
#body={"prompt":"Im Folgenden findest du eine Instruktion, die eine Aufgabe bescheibt. Schreibe eine Antwort, um die Aufgabe zu lösen.\n\n### Instruktion:\n"+message+"\n\n### Antwort:","max_tokens":500, "echo":"False","stream":"True"}
body={"prompt":" chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n\nUSER:\n"+message+"\n\nASSISTANT:","max_tokens":500, "echo":"False","stream":"True"}
response=""
buffer=""
print("URL: "+url)
print("User: "+message+"\nAI: ")
for text in requests.post(url, json=body, stream=True): #-H 'accept: application/json' -H 'Content-Type: application/json'
if buffer is None: buffer=""
buffer=str("".join(buffer))
#print("*** Raw String: "+str(text)+"\n***\n")
text=text.decode('utf-8')
if((text.startswith(": ping -")==False) & (len(text.strip("\n\r"))>0)): buffer=buffer+str(text)
#print("\n*** Buffer: "+str(buffer)+"\n***\n")
buffer=buffer.split('"finish_reason": null}]}')
if(len(buffer)==1):
buffer="".join(buffer)
pass
if(len(buffer)==2):
part=buffer[0]+'"finish_reason": null}]}'
if(part.lstrip('\n\r').startswith("data: ")): part=part.lstrip('\n\r').replace("data: ", "")
try:
part = str(json.loads(part)["choices"][0]["text"])
print(part, end="", flush=True)
response=response+part
buffer="" # reset buffer
except Exception as e:
print("Exception:"+str(e))
pass
yield response
gr.ChatInterface(response).queue().launch(share=True) #False, server_name="0.0.0.0", server_port=7864)
print("Interface up and running!") |